Forest 4.0 – Research Infrastructure to Support the Operationalization of Digitalization in Maintenance and Management of Forest Ecosystems

Forest ecosystems and forestry face challenges from increased timber demand, climate change, evolving global markets, rural depopulation, and growing emphasis on forests' social values. As critical carbon sinks, biodiversity reservoirs, and sources of sustainable materials, forests are vital for climate change mitigation and rural employment. However, climate change and past management practices are intensifying natural disturbances, such as storms, droughts, and wildfires. Addressing these challenges requires innovative approaches, including the integration of advanced digital technologies associated with the Fourth Industrial Revolution, such as Artificial Intelligence (AI), the Internet of Things (IoT), blockchain, and big data analytics. These technologies collectively form the foundation of the Forest 4.0 concept, which aims to enhance forest management practices. This presentation introduces the ambitions and achievements of the newly established Lithuanian research infrastructure, Forest 4.0. Developed as part of the Forest 4.0 Teaming for Excellence project, this initiative integrates research facilities and expertise from major forestry research centers at Vytautas Magnus University and the Lithuanian Research Centre for Agriculture and Forestry. The presentation highlights several case studies showcasing innovative methods for collecting, integrating, and analyzing heterogeneous environmental data. One example is the modernization of the Lithuanian National Forest Inventory to explore new aspects of forest ecosystems, such as carbon sequestration, tree micro-habitat assessment, and genetic diversity monitoring. Another example involves the digitalization of observation processes at the Aukštaitija and Žemaitija stations of integrated monitoring, which are part of the Lithuanian eLTER network. Research topics covered in these cases include forest ecosystem dynamics under a changing climate, AI-driven monitoring and prediction techniques for forest management and threat detection, the use of remote sensing and ubiquitous computing to advance geospatial methods, modeling forest processes, conducting multimodal data analyses, and developing decision-support tools to improve forest management practices.